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Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging.

NeuroImage
Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important that the WM tracts can be accurately and reproducibly characterized fr...

A deep learning algorithm may automate intracranial aneurysm detection on MR angiography with high diagnostic performance.

European radiology
OBJECTIVES: To develop a deep learning algorithm for automated detection and localization of intracranial aneurysms on time-of-flight MR angiography and evaluate its diagnostic performance.

Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm.

Computers in biology and medicine
MOTIVATION: Brain or central nervous system cancer is the tenth leading cause of death in men and women. Even though brain tumour is not considered as the primary cause of mortality worldwide, 40% of other types of cancer (such as lung or breast canc...

Using machine learning to predict early readmission following esophagectomy.

The Journal of thoracic and cardiovascular surgery
OBJECTIVE: To establish a machine learning (ML)-based prediction model for readmission within 30 days (early readmission or early readmission) of patients based on their profile at index hospitalization for esophagectomy.

Lomboaortic Lymphadenectomy in Gynecological Oncology: Laparotomy, Laparoscopy or Robot-Assisted Laparoscopy?

Annals of surgical oncology
BACKGROUND: The outcomes of paraaortic lymphadenectomy were compared for the treatment of gynecological malignancies to identify the most appropriate surgical approach.

CAST: A multi-scale convolutional neural network based automated hippocampal subfield segmentation toolbox.

NeuroImage
In this study, we developed a multi-scale Convolutional neural network based Automated hippocampal subfield Segmentation Toolbox (CAST) for automated segmentation of hippocampal subfields. Although training CAST required approximately three days on a...

Potential of deep learning in assessing pneumoconiosis depicted on digital chest radiography.

Occupational and environmental medicine
OBJECTIVES: To investigate the potential of deep learning in assessing pneumoconiosis depicted on digital chest radiographs and to compare its performance with certified radiologists.

Effectiveness of robot-assisted gait training on patients with burns: a preliminary study.

Computer methods in biomechanics and biomedical engineering
Gait enables individuals to move forward and is considered a natural skill. However, gait disturbances are very common in patients with burn injury. Recent studies have emphasized the role of robot-assisted gait training (RAGT) in rehabilitation. Thi...